{"id":"W2621873095","doi":"10.1109/tac.2017.2714102","title":"Distributed Sensor Coordination Algorithms for Efficient Coverage in a Network of Heterogeneous Mobile Sensors","year":2017,"lang":"en","type":"article","venue":"IEEE Transactions on Automatic Control","topic":"Energy Efficient Wireless Sensor Networks","field":"Computer Science","cited_by":24,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"National Institute of Standards and Technology","keywords":"Computer science; Software deployment; Wireless sensor network; Distributed computing; Reduction (mathematics); Distributed algorithm; Process (computing); Real-time computing; Field (mathematics); Algorithm; Computer network; Mathematics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001354114,0.0008649539,0.0009628499,0.0007845456,0.0005600757,0.0009022369,0.001370496,0.0007399078,0.0009137043],"category_scores_gemma":[0.003398679,0.0003675408,0.0005207183,0.001155802,0.0008635391,0.001119073,0.001454917,0.0008128018,0.0002157996],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009002819,"about_ca_system_score_gemma":0.0007621577,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001935499,"about_ca_topic_score_gemma":0.001428079,"domain_scores_codex":[0.9993075,0.0002452122,0.00003989926,0.000136009,0.0002054591,0.00006590162],"domain_scores_gemma":[0.9990699,0.0005620194,0.0001236409,0.00007984565,0.000128022,0.00003669106],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00005646202,0.00001906148,0.000245875,0.00005695388,0.00002270976,0.00004779041,0.00008119667,0.934455,0.001622982,0.02471588,0.0007352513,0.03794082],"study_design_scores_gemma":[0.000018365,0.00002718692,0.00005524035,0.000004454473,0.000005347671,0.00002461816,0.00001220327,0.9921555,0.0004466353,0.006611026,0.0006352643,0.000004215616],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.004896707,0.0003337858,0.9939516,0.00007484887,0.00001811009,0.00002210752,0.00001131505,0.00007625455,0.0006152568],"genre_scores_gemma":[0.6135041,0.001148787,0.3824809,0.00008509978,0.0001100012,0.0003909781,0.0001169103,0.00008275629,0.002080486],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001935499,"threshold_uncertainty_score":0.007161319,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01087607796014293,"score_gpt":0.2472325221802012,"score_spread":0.2363564442200583,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}